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Research Associate in Artificial Intelligence Powered Framework for OnLine Production Scheduling

The University of Manchester

Manchester

Hybrid

GBP 40,000 - 60,000

Full time

3 days ago
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Job summary

The University of Manchester seeks a qualified individual to develop a next generation autonomous online scheduling framework using machine learning. This role includes evaluating energy consumption, preparing models, and collaborating with academic and industrial partners. The ideal candidate will possess strong expertise in process systems engineering and optimisation.

Benefits

Market leading Pension scheme
Excellent employee health and wellbeing services
Exceptional starting annual leave entitlement
Additional paid closure over Christmas
Local and national retailer discounts

Qualifications

  • Strong expertise in process systems engineering and machine learning.
  • Experience in optimisation and mathematical modelling is essential.

Responsibilities

  • Deliver an autonomous online scheduling framework for chemical manufacturing.
  • Evaluate energy consumption and prepare process scheduling models.
  • Collaborate with academics and industrial partners for system testing.

Skills

Process systems engineering
Mathematical modelling
Optimisation
Machine learning
Artificial intelligence

Job description

Overall purpose of the job:

This position is to deliver a next generation autonomous online scheduling framework in response to different types of disruptions in the chemical manufacturing industry using machine learning techniques. You will be responsible for the evaluation of energy consumption for industrial data reconciliation and preparation of process scheduling models, quantification of different types of uncertainty and the development of data-driven autonomous techniques for online scheduling. You will collaborate seamless with academics from University College London for such development. You will also work closely with the industrial partners to test the new online scheduling framework in a practical context and demonstrate the benefit.

The position requires strong expertise in process systems engineering, mathematical modelling, optimisation, machine learning, and artificial intelligence.

What you will get in return:
  • Fantastic market leading Pension scheme
  • Excellent employee health and wellbeing services including an Employee Assistance Programme
  • Exceptional starting annual leave entitlement, plus bank holidays
  • Additional paid closure over the Christmas period
  • Local and national discounts at a range of major retailers
As an equal opportunities employer we welcome applicants from all sections of the community regardless of age, sex, gender (or gender identity), ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.

Our University is positive about flexible working - you can find out more here

Hybrid working arrangements may be considered.

Please note that we are unable to respond to enquiries, accept CVs or applications from Recruitment Agencies.

Any recruitment enquiries from recruitment agencies should be directed to People.Recruitment@manchester.ac.uk . Any CV's submitted by a recruitment agency will be considered a gift.

Enquiries about the vacancy, shortlisting and interviews:

Name: Dr Jie Li

Email: jie.li-2@manchester.ac.uk

Or

Name: Dr Dongda Zhang

Email: Dongda.zhang@manchester.ac.uk

General enquiries:

Email: People.recruitment@manchester.ac.uk

Technical support:

https://jobseekersupport.jobtrain.co.uk/support/home

This vacancy will close for applications at midnight on the closing date.

Please see the link below for the Further Particulars document which contains the person specification criteria.
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